EP0660282A1 - Système pour la détection de débuts d'includies - Google Patents

Système pour la détection de débuts d'includies Download PDF

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Publication number
EP0660282A1
EP0660282A1 EP94119614A EP94119614A EP0660282A1 EP 0660282 A1 EP0660282 A1 EP 0660282A1 EP 94119614 A EP94119614 A EP 94119614A EP 94119614 A EP94119614 A EP 94119614A EP 0660282 A1 EP0660282 A1 EP 0660282A1
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EP
European Patent Office
Prior art keywords
signal
fire
alarm system
fire alarm
fuzzy logic
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
EP94119614A
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German (de)
English (en)
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EP0660282B1 (fr
Inventor
Marc Pierre Dr. Thuillard
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Siemens AG
Original Assignee
Cerberus AG
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Filing date
Publication date
Application filed by Cerberus AG filed Critical Cerberus AG
Publication of EP0660282A1 publication Critical patent/EP0660282A1/fr
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B17/00—Fire alarms; Alarms responsive to explosion

Definitions

  • the present invention relates to a fire detection system for early detection of fires, with at least one linear smoke, a scattered light or a flame detector and with a signal processing stage containing an evaluation circuit and a fuzzy logic for the signals generated in the at least one detector.
  • the signal is integrated by one or more fire detectors, which are not specified in more detail, and in addition to the detector information, environmental information such as temperature, time of day or building height is determined and collected. All this information is then linked to fuzzy logic.
  • a number of further sensors are used in order to obtain unambiguous information from the different types of sensor signals.
  • Linear smoke detectors such as the type A2400 detector offered by Cerberus AG, contain a transmitter that emits a modulated infrared beam and a receiver that collects and evaluates the incoming infrared radiation.
  • the detector has a long monitoring distance of at least 3 meters, for example; Smoke entering the beam weakens the infrared radiation.
  • Flame detectors such as the S2406 infrared detector offered by Cerberus AG, contain two pyroelectric sensors that are sensitive to specific wavelengths and can detect a fire at a relatively large distance, for example, over 20 meters.
  • Linear smoke detectors are sensitive to various disturbance variables, which can be roughly divided into two classes.
  • One category is environmental disturbances, such as fluctuations in the refractive index of the air at elevated temperature or condensation or water droplets on the optics of the detector when there is increased humidity, or electromagnetic interference from radio telephones and the like.
  • the other category of interference is interference, for example interruptions in the light beam by a person, an object or a machine, or movements of the walls supporting the detectors.
  • the detector signal is interpreted as a fire. Strong electromagnetic interference and, in systems with a strong airflow mixture, streaks are often interpreted as a fire. These disturbances cannot be suppressed with known arrangements, including those of the type described in EP-A-0 419 668.
  • Flame detectors that do not actively emit a beam and analyze it after receipt, but that examine the incident radiation, which can also be formed by indirect radiation, are quite insensitive and react to most of the disturbance variables mentioned in connection with the linear smoke detectors at most on interference radiation.
  • the invention is now to provide a fire alarm system of the type mentioned at the outset in which faults are recognized as such and thus false alarms suppressed as much as possible and in addition, the causes of faults are diagnosed as automatically as possible.
  • the signal processing stage contains means for time analysis of the signals for the estimation of at least two signal parameters, and in that the signal parameters form linguistic variables of the fuzzy logic.
  • a first preferred embodiment of the system according to the invention is characterized in that the signal parameters are formed by the signal gradient and the signal noise.
  • a second preferred embodiment of the arrangement according to the invention is characterized in that the signal parameters are formed by the signal asymmetry and the signal jumps.
  • linear smoke detectors consist of a transmitter that emits a modulated infrared beam and a receiver that collects the incoming infrared radiation and evaluates it in an electronic circuit.
  • the transmitter and receiver can be arranged opposite one another or next to one another, in the latter case reflectors being provided on the side opposite the transmitter and receiver.
  • the main components of the receiver include an optical system 1, a photodiode 2 and a signal processing stage 3 with an estimation stage 4 and a fuzzy controller 5.
  • the signal processing stage 3 contains an evaluation circuit in which the amplified signal of the photodiode 2 is compared with an adjustable alarm threshold is, and a tracking circuit to compensate for slow changes in the received signal due to dust or aging of the components.
  • the evaluation circuit and the tracking circuit are known from the A2400 linear smoke detector from Cerberus AG and are not described in more detail here. Smoke entering the infrared beam weakens the infrared radiation and causes a corresponding weakening of the received signal. As soon as this drops below a certain value, the receiver triggers an alarm signal.
  • the alarm triggering is exclusively dependent on the result of the comparison of the received signal with the alarm threshold
  • the alarm signal is examined with suitable fuzzy algorithms and the alarm is either confirmed or recognized as a false alarm.
  • a time analysis of the received signal is carried out with a Calculation of several signal parameters as well as a connection of the signal parameters and their division into different event categories using fuzzy logic.
  • the output signal of the photodiode 2 reaches the estimation stage 4, where, on the one hand, the received signal is smoothed and, on the other hand, various signal parameters or signal properties derived from the received signal are estimated.
  • the raw value of the received signal is normalized by dividing the respective signal change ⁇ l by a reference value lo.
  • the ratio of raw value to signal is examined and a constant is added to or subtracted from the signal.
  • the signal parameters or signal properties are noise, gradient, jumps and asymmetry. These parameters are calculated as part of a time analysis of the smoothed signal using signal filters and intercorrelation functions.
  • the noise is determined by comparing successive raw values, the gradient as a moving average of several measuring points, the asymmetry based on a comparison between the raw value on the one hand and the smoothed signal and noise on the other hand, and a jump indicator representative of the signal jumps by comparing the signal smoothed over differently long intervals .
  • the gradient is estimated in such a way that the gradient is small with a very small steepness or with a jump and is large with an increase over a longer period. Functionally, this corresponds to a band pass.
  • the fuzzy controller 5 contains three stages ST1 to ST3.
  • the first stage ST1 is fuzzy, that is, the conversion of the sharp numbers obtained from the various signal parameters into unsharp quantities, the so-called fuzzy sets.
  • the rules set up during the design of the fuzzy controller are applied to the fuzzy sets, and in the third stage ST3, the defuzzification takes place, that is, the calculation of the sharp output variables.
  • the basics of fuzzy logic reference is made to the now extensive literature on this topic, for example to the book “Fuzzy Set Theory and its Applications” by H.J. Zimmermann, Kluwer Academic Publishers, 1991.
  • Fuzzyfication in the first stage ST1 of the fuzzy controller 5 takes place by means of the fuzzy sets shown in FIGS. 2a to 2d.
  • 2a shows the fuzzy sets for the signal parameter noise, FIG. 2b those for the gradient, FIG. 2c for the jumps and FIG. 2d the fuzzy sets for the asymmetry. Since in all fuzzy sets shown the upper limit for the membership function plotted on the ordinate or for the degree of membership is equal to one, it is in any case normal fuzzy sets.
  • the individual signal parameters are the linguistic variables of the fuzzy logic and these linguistic variables can have different values, which are the names for the fuzzy sets shown in FIGS. 2a to 2d.
  • the linguistic variable noise can take one of three values (small, medium, large); the linguistic variable gradient (FIG. 2b) also one of three values (small, medium, large); the linguistic variable jumps (Fig. 2c) one of four values (very small, small, medium, large); and the linguistic variable asymmetry (Fig. 2d) one of only two values (small, large).
  • FIG. 3 shows a knowledge base built up from data obtained in practice with the values or linguistic variables of the individual signal parameters and with typical combinations of these values for certain frequent fire events and faults.
  • the typical disturbances which for the most part are also entered in the second stage ST2 of the fuzzy controller 5 (FIG. 1), are splash water on the optics, complete or partial coverage of the infrared beam by a person crossing it or by a person Subject to condensation on the optics at high humidity and strong cooling, to electromagnetic interference (EMI), to scissors, as they occur in places with high local heat development, such as in or around factories or in thermal power plants, and to test filters. As is well known, the latter are used to trigger an alarm as part of maintenance or revision work.
  • the information test filter then means that either a test filter is inserted or the beam was partially covered within a very short time.
  • stage ST2 (FIG. 1), if the level falls below the alarm threshold due to the smoothed reception signal, the knowledge base shown in FIG. 3 is used to investigate whether it is actually a fire or just a fault.
  • the fuzzy rules that are used are formulated in such a way that the following applies: if (one of the four conditions mentioned and signal ⁇ alarm threshold) then fire.
  • the system described is suitable not only for false alarm suppression, but also for fault diagnosis.
  • Today's linear smoke detectors are already designed that certain faults, in particular an interruption of the infrared beam or a failure of the transmitter, cause an interruption in the circuit to the line terminating terminals of the receiver, as a result of which a line interruption is simulated. If it is determined during the troubleshooting that there is no voltage at the terminals mentioned, then the possible causes (receiver cover not installed, light beam interrupted, transmitter failure, receiver fault) are checked one after the other.
  • the fault diagnosis can be expanded to include considerably more faults and can also be carried out much more simply by also setting up fuzzy rules for the faults, which allows the probable cause of the fault (s) to be displayed directly. This makes troubleshooting much easier and cheaper, and you also have the option of eliminating the cause of frequently occurring faults.
  • a further possibility of using the information obtained by means of the fuzzy logic is to automatically adapt the detector sensitivity, for example by selecting a higher alarm threshold when streaks occur, or by taking other measures, for example to switch on the heating of the relevant front cover when condensation occurs .
  • fuzzy controller changes little. Only certain other fuzzy sets need to be defined and other fuzzy rules drawn up. However, since the possible causes of faults are very similar for all three detector types, the necessary adjustments are within the scope of the skill of the person skilled in the art.

Landscapes

  • Business, Economics & Management (AREA)
  • Emergency Management (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Fire Alarms (AREA)
  • Fire-Detection Mechanisms (AREA)
  • Photometry And Measurement Of Optical Pulse Characteristics (AREA)
  • Alarm Systems (AREA)
EP94119614A 1993-12-20 1994-12-12 Système pour la détection de débuts d'incendies Expired - Lifetime EP0660282B1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
CH3793/93 1993-12-20
CH03793/93A CH686914A5 (de) 1993-12-20 1993-12-20 Brandmeldesystem zur Frueherkennung von Braenden.
CH379393 1993-12-20

Publications (2)

Publication Number Publication Date
EP0660282A1 true EP0660282A1 (fr) 1995-06-28
EP0660282B1 EP0660282B1 (fr) 2000-08-09

Family

ID=4263585

Family Applications (1)

Application Number Title Priority Date Filing Date
EP94119614A Expired - Lifetime EP0660282B1 (fr) 1993-12-20 1994-12-12 Système pour la détection de débuts d'incendies

Country Status (8)

Country Link
EP (1) EP0660282B1 (fr)
JP (1) JPH07200961A (fr)
CN (1) CN1038622C (fr)
AT (1) ATE195386T1 (fr)
CH (1) CH686914A5 (fr)
DE (1) DE59409474D1 (fr)
FI (1) FI111666B (fr)
NO (1) NO324427B1 (fr)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0751488A1 (fr) * 1995-06-30 1997-01-02 Hochiki Corporation Détecteur terminal pour un système de prévention de sinistres
EP1150108A1 (fr) * 2000-04-26 2001-10-31 BODENSEEWERK GERÄTETECHNIK GmbH Méthode et dispositif de détection précoce d'une surchauffe possible d'un objet
DE10046992C1 (de) * 2000-09-22 2002-06-06 Bosch Gmbh Robert Streulichtrauchmelder
US7286704B2 (en) 2000-03-09 2007-10-23 Robert Bosch Gmbh Imaging fire detector
CN103956018A (zh) * 2014-05-15 2014-07-30 杜玉龙 一种改进的建筑消防设施报警信号分析处理方法
CN107067683A (zh) * 2017-04-14 2017-08-18 湖南省湘电试研技术有限公司 一种输电线路山火聚类定量预报方法及系统

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6879253B1 (en) * 2000-03-15 2005-04-12 Siemens Building Technologies Ag Method for the processing of a signal from an alarm and alarms with means for carrying out said method
US8659415B2 (en) * 2011-07-15 2014-02-25 General Electric Company Alarm management
CN110111548A (zh) * 2019-04-14 2019-08-09 杭州拓深科技有限公司 一种消防报警设备的补偿优化方法

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0419668A1 (fr) * 1989-01-25 1991-04-03 Nohmi Bosai Kabushiki Kaisha Systeme d'alarme contre les incendies

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1284580A1 (fr) * 2001-08-16 2003-02-19 Swisscom Mobile AG Système et procédé pour effectuer une mise a jour de position dans un réseau radio-mobile de type GSM
WO2005021223A1 (fr) * 2003-08-27 2005-03-10 Koninklijke Philips Electronics N.V. Appareil de rasage comportant un dispositif de coupe des cheveux courts et un dispositif de coupe des cheveux longs

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0419668A1 (fr) * 1989-01-25 1991-04-03 Nohmi Bosai Kabushiki Kaisha Systeme d'alarme contre les incendies

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0751488A1 (fr) * 1995-06-30 1997-01-02 Hochiki Corporation Détecteur terminal pour un système de prévention de sinistres
US5715177A (en) * 1995-06-30 1998-02-03 Hochiki Corporation Terminal sensing device for a disaster prevention monitoring system
US7286704B2 (en) 2000-03-09 2007-10-23 Robert Bosch Gmbh Imaging fire detector
EP1150108A1 (fr) * 2000-04-26 2001-10-31 BODENSEEWERK GERÄTETECHNIK GmbH Méthode et dispositif de détection précoce d'une surchauffe possible d'un objet
US6646558B2 (en) 2000-04-26 2003-11-11 Bodenseewerk Gerätechnik GmbH Method and arrangement for recognizing potential overheating of an object
DE10046992C1 (de) * 2000-09-22 2002-06-06 Bosch Gmbh Robert Streulichtrauchmelder
CN103956018A (zh) * 2014-05-15 2014-07-30 杜玉龙 一种改进的建筑消防设施报警信号分析处理方法
CN107067683A (zh) * 2017-04-14 2017-08-18 湖南省湘电试研技术有限公司 一种输电线路山火聚类定量预报方法及系统
CN107067683B (zh) * 2017-04-14 2018-01-09 湖南省湘电试研技术有限公司 一种输电线路山火聚类定量预报方法及系统

Also Published As

Publication number Publication date
NO324427B1 (no) 2007-10-15
FI945934A (fi) 1995-06-21
CN1038622C (zh) 1998-06-03
FI945934A0 (fi) 1994-12-16
EP0660282B1 (fr) 2000-08-09
CH686914A5 (de) 1996-07-31
FI111666B (fi) 2003-08-29
ATE195386T1 (de) 2000-08-15
CN1127394A (zh) 1996-07-24
JPH07200961A (ja) 1995-08-04
NO944821L (no) 1995-06-21
NO944821D0 (no) 1994-12-13
DE59409474D1 (de) 2000-09-14

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